It is estimated that 2 billion people are infected with M. tuberculosis, an important human pathogen that causes significant morbidity and mortality worldwide. A better understanding of the molecular mechanisms of M. tuberculosis pathogenesis is necessary for the rational design of the next generation of drugs and vaccines. Our goal is to elucidate host signaling mechanisms exploited by M. tuberculosis for growth and persistence in macrophages. Our central hypothesis is that kinase signaling leads to a gene expression program in infected macrophages that promotes an insufficient response to infection thereby facilitating Mtb growth and survival. We have identified several kinases in macrophages that function to support M. tuberculosis replication during infection, indicating either that they re activated by M. tuberculosis as part of a virulence strategy or that they are negative regulators of innate anti-microbial pathways. Of specific relevance to this proposal are inhibitors of the mammalian kinases AKT and EGFR that disrupt the ability of M. tuberculosis to replicate in human primary macrophages. Our approach is to utilize recent advances in global proteomic and phosphoproteomic technologies to characterize macrophage-signaling pathways that are activated by infection with M. tuberculosis. In addition, we will use these technologies to elucidate the functional phosphoproteome by identifying of downstream targets of AKT and EGFR in M. tuberculosis infected macrophages. In aim 1, we describe the use of proteomics and phosphoproteomics to characterize signaling events resulting from M. tuberculosis infection of human primary monocyte-derived macrophages with high temporal resolution using 2D gel electrophoresis and mass-spectrometry based proteomics and phosphoproteomics to monitor phosphorylation sites on a global scale. In aim 2 we utilize the same strategy to identify differences in the proteome and phosphoproteome in the context of inhibition of AKT and, independently, EGFR. Results from the proteomic profiling will be integrated with existing transcriptomic and screening datasets to further refine the architecture of the signaling network activated by M. tuberculosis infection. In addition, the results will be used to motivate future hypothesis driven experiments seeking to describe the molecular mechanisms by which key kinase regulators support M. tuberculosis virulence in macrophages.